Optimum fusion of correlated local decisions

E. Drakopoulos*, Chung Chieh Lee

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

A distributed detection system consisting of a number of local detectors and a fusion center is considered. Each detector makes a decision for the underlying binary hypothesis testing problem based on its own observations and transmits its decision to the fusion center where the global decision is derived. The local decision rules are assumed to be given, but the local decisions are correlated. The correlation model is expressed by a finite number of conditional probabilities. The optimum decision fusion rule in the Neyman-Pearson sense is derived and analyzed. The performance of the distributed detection system versus the degree of correlation between the local decisions is studied for a special correlation structure that can be indexed by a single parameter. It is shown that system performance degrades as the degree of correlation between local decisions increases.

Original languageEnglish (US)
Pages (from-to)2489-2494
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - Dec 1 1988

ASJC Scopus subject areas

  • Chemical Health and Safety
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality

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